Apache Polaris™ (incubating) Meetup Bay Area
Bay Area Apache Polaris™ (incubating) Meetup!
Join us on January 27th (Tuesday) from 5:30-8:30 PM at the Snowflake Menlo Park Office.
Connect with fellow community members, share insights, and dive into the latest developments in the world of Apache Polaris!
Note on Parking: There is free parking available at the event.
Agenda
5:30 PM - 6:15 PM: Doors Open & Networking
6:15 PM - 8:15 PM: Welcome Remarks & Presentations!
8:15 PM - 9:00 PM: More Networking
The event will focus on use cases of and new developments in Apache Polaris (https://polaris.apache.org/)
Join us before the meetup for a hands-on Polaris Community Sprint.
Sessions
Catalog-Driven Access and Acceleration in Modern Lakehouse Architectures, Kevin Shen @ VeloDB
Open table formats and centralized catalogs are becoming the foundation of modern Lakehouse architectures. In this talk, we explore how Apache Iceberg and Apache Polaris enable unified metadata management, secure authentication and authorization, and interoperability across multiple query engines. We then discuss how Apache Doris fits into this architecture, accelerating Iceberg analytics while integrating deeply with external catalogs through credential vending and JWT-based delegated access.
Finally, a demo using VeloDB demonstrates querying Iceberg data via Apache Polaris, highlighting how open catalogs and open table formats enable a decoupled and high-performance Lakehouse.
Graph Analytics on Iceberg with Apache Polaris — No ETL Required, Weimo Liu @ Puppygraph
Apache Polaris is quickly becoming a cornerstone for teams standardizing on Apache Iceberg with centralized governance and cross-engine access. But while SQL works well for aggregations and reporting, many real-world workloads depend on understanding relationships—across users, systems, events, and dependencies.
In this talk, we’ll explore how teams can add real-time graph analytics on top of Iceberg data governed by Apache Polaris, without copying data into a graph database or building ETL pipelines.
We’ll walk through:
How Apache Polaris enables open, governed access to Iceberg tables
When graph queries outperform complex multi-join SQL
How PuppyGraph runs multi-hop graph traversals directly on Iceberg via Polaris
Practical use cases like fraud detection, cloud security analysis, observability, and GraphRAG
Attendees will leave with a clear mental model for combining Polaris + Iceberg + graph analytics to answer questions SQL struggles with while using the data they already have.
Building Audit, Automation, and Integrations with Polaris Events, Adnan Hemani @ Snowflake
Apache Polaris exposes critical control-plane activity in Iceberg-based platforms, enabling observation and integration beyond the catalog API itself. This talk introduces the Polaris Events architecture, explaining what types of events are emitted, how they are structured, and how they flow from catalog operations to downstream consumers. We’ll explore practical use cases such as auditing and compliance, operational monitoring, metadata-driven automation, and integration with external governance and platform services. Finally, we’ll show upcoming planned improvements - and where you can help!
Bringing AI Native Storage to the Open Multimodal Lakehouse: Apache Polaris Meets Lance, Jack Ye @ LanceDB
This talk introduces how Apache Polaris and the Lance ecosystem are coming together to enable an open and AI-native multimodal lakehouse. We will briefly cover what makes Lance an AI-oriented format for vector search, full-text search, and SQL analytics on the same storage, and clarify the broader multimodal lakehouse vision of unifying embeddings, features, unstructured data, and structured tables under a shared open framework.
We then focus on the practical integration work between Polaris and Lance, including the Lance Namespace design, how Lance’s Rust core surfaces Polaris integrations with key features like credential vending through its Python and Java bindings. We will show how this fits cleanly within the Polaris catalog architecture, how Lance tables can coexist with Iceberg tables under a unified metadata plane, and how engines such as Spark, Trino, Ray, LanceDB, and DuckDB can take advantage of this integration. Attendees will leave with a clear understanding of how Lance expands the Polaris ecosystem to support AI and multimodal workloads in a secure, open, and engine-agnostic way.
About PuppyGraph
PuppyGraph is the first and only real time, zero-ETL graph query engine in the market, empowering companies to transform existing relational data stores into a unified graph model in under 10 minutes, bypassing traditional graph databases' cost, latency, and maintenance hurdles.
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About Snowflake
Snowflake makes enterprise AI easy, efficient and trusted. More than 10,000 companies around the globe, including hundreds of the world’s largest, use Snowflake’s AI Data Cloud to share data, build applications, and power their business with AI. Snowflake provides native support for Apache Iceberg™ and Apache Polaris™ (incubating).
📚 Check out how Snowflake can power your open data lakehouse
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About VeloDB
VeloDB powered by Apache Doris is the fastest real-time analytical database for diverse workloads, bringing real-time analytics wherever your data lives. Leveraging advanced indexing and storage optimization, VeloDB enables real-time analytics across streaming, databases, data warehouses, and lakehouses, enabling interactive BI, AI-driven workloads, and enterprise analytics with unmatched performance and cost effectiveness
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